Abstract
As a side effect of unprecedented amount of digitization of data, classical retrieval tools found themselves unable to go further beyond the tip of the Iceberg. Data Mining in conjunction with the Formal Concept Analysis, is a clear promise to furnish adequate tools to do so and specially to be able to derive concise generic and easy understandable bases of “hidden” knowledge, that can be reliable in a decision making process. In this paper, we propose to revisit the notion of association rule redundancy and to present sound inference axioms for deriving all association rules from generic bases of association rules.
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Yahia, S.B., Nguifo, E.M. (2004). Revisiting Generic Bases of Association Rules. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2004. Lecture Notes in Computer Science, vol 3181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30076-2_6
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DOI: https://doi.org/10.1007/978-3-540-30076-2_6
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